Schibsted YAMS
How to build and maintain a thousands/req service with minimal dedication
daniel(dot)caballero at schibsted(dot)com
Who are you?
I'm sorry. I did NOT write BSD
So... I work
... I (some kinda) teach
... I (try to) program...
... I (would like to) rock...
... and I live
So... I value my time (a lot)
And I really don't like to waste it
- In resolving incidents
- In repetitive work
Schibsgrñvahed..WHAT??
What is Schibsted?
And SPT?
It's about convergence through global solutions
What's behind global components / services?
You build it, you run it
Nothing new in the horizon probably for you
- first mention in 2006, by Werner Vogels / Amazon
- Nice elaboration behind the rationale here
That means there's no ops/support/systems/devops team.
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CDNs able to transform contents:
- As a native functionality...
- Or through lambdas
SaaS solutions:
- imgix
- libpixel
- Cloudinary
Opensource solutions:
So why?
- Sites were doing already that. So saving sites time
- Close to the Schibsted sites
- not just latency (multiregion); also feature-set, compliance...
- Cost effective
- SaaS are expensive at Schibsted scale
- We can build & maintain what we really need
- Adapting to other needs:
- Document transformation
- Video streaming
Why not offline transformations?
Lots of (user) contents given the classified business. Sites are dynamic by nature. Some of them do adapt the request to the device. Blocking redesigns or improvements because lack of capacity to reprocess
What are you very proud about?
High usage
Does not require high maintenance
(Almost) No incidents. We would be able to maintain this with half an engineer
- We dont like to cut people in half, so let's say one engineer
But be careful: if you stop developing a service, you kill a service
- Stops being competitive
- It quickly becomes legacy (old stack, old libs, old design)
- Disconnect from current business needs
So we try to convince the company it requires, at least, the focus of two engineers.
Low costs
Low latency
How did you achieved that?
Combination of...
- Team
- Product management
- Technical
Team
Autonomy
Benefiting from other Sch services
Big department portfolio:
- AWS bootstrap
- Vulnerability scans
- TravisCI, Artifactory
Collaboration + transparency mindset
Internal RFCs Consumers as contributors Internal opensource model (full visibility of Github repos)
Product
Actual need
Limited scope
API as the point of interaction No business logic. "Dumb" service Almost no-functionality that is used by a single site or no-one
Tech
Everything as code
No space for "one time" actions.
- Alerting configuration by code
- Infrastructure updates
Good design choices
(but not perfect / or the best, for sure)
- Immutable pattern
- AWS + Netflix stack + Microservices
- libvips
Continuous Delivery
And capacity to incorporate everything to the pipeline. > Looking forward, rather than investing lots of time in your rollback strategy
Small deltas. Iterative deliveries. Low risk deployments.
0-error target
Yeah, Google SRE book and error budgets...
... but helped us to understand, tune, and get the trust from Sch sites, avoiding major disruptions when big sites onboarded, and minimizing the chance of "unplanned / reactive" activities
We also rely in a "good enough" test suite (unit+integration+acceptance) with a good coverage of all API-functionality
- New error conditions means new tests
- If tests are green, almost (TM) no space for surprises
Troubleshooting toolkit
And what did you do wrong?
The Refactor (TM)
Complete refactor. New platform in parallel to deliver a new version of the API
- APIv0
- APIv1
Microservices split
Domain driven design... coupling of some services
Nice solution... but
Why not docker/k8s?
- Local tests
- YAMS Portal/Frontend already there
- Migration exercise
gRPC?
Why not a Service Mesh?
And Prometheus?
We may.
And it may be a good moment to consider opencensus.
Actual (& not so far) future
More elasticity to reduce costs
- Changes in transformation rules means massive eviction
- So we are a bit overscaled...
- Better degradation and more efficient ASG triggers
- Reusing cache if no capacity
- Automatic ASG parameters adjustments
- Minimize parallelization in the transformation pipe
- Incoming queue
Extra compression
Bringing the service closer to the business
- Image uploader
- Online image editor
- Integration with data services
- Automatic classification
- Nudity detector
- Car plate pixelation
- More regions/cloud providers deployments
- Video transcoding...
Actual transformation pipelines
More adoption?
Some major Marketplaces are not using the service, yet
Simulating dependencies failures
Hoverfly: similar in concept to the Simian Army from Netflix, but specialized in API degradations
Stress test as part of the pipeline
Before closing...
Are you going to opensource it?
- Schibsted do support contribution to opensource projects
- As well as releasing internal code
- Problem: Not following a "contribute-first" approach
- But already contributed to bimg, zuul, krakenD...
Are you going to offer this SaaS to other companies?
Latencymap
api noiser
Corollary
Be Rx in the code...
But not in real life
Great thanks...
Sch*
And especially...
Edge colleagues
Other Qs?
dan . caba at google (dot)com
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